Playlist features heatmap

I created a heatmap with the average value of the different audio features in different playlists. From this graph we can see that the corpus overall has a low valence level and high energy and danceability. The loudness value is been scaled from 0 to 1. The pink playlist has a higher valence and loudness compare to other playlists. The blue playlist has the highest energy value. And the black and white playlist have a relatively high daceability. As the corpus is electornic music, it has very high instrumentalness level and low acousticness level in all four playlists so these attributes are not invovled in this heatmap.

Valence-Energy graph

From this graph we can see that the pink category has a combination of sounds with high energy and low valence, or high valence with relatively low energy. The black category has high energy, with valence spread out the scale, but mainly at a low level. The blue category has medium - high energy with medium valence. The white category has medium energy and low valence.

Pink

For the pink playlist I created the chroma and timbre self similarity matrix for two songs: “Sakha-Infinity Remix” and “Cirrus Apparition”. Overall the pink playlist shows clear structure of music in the self similarity matrix, as most of the matrices have dark checkerboard patterns. There is a main melody going throughout the song and some parts with some variations. For “Sakha” we can see 4 different parts in the track. The change of chroma and timbre are almost at the same time, and there is a fade out in the end. For “Cirrus Apparition”, the chroma is almost the same across the whole song, but from timbre there are two small segement at around 200s and 300s where variation happens.

Click here to listen to Sakha-Infinity Remix
Click here to listen to Cirrus Apparition

Blue

For the blue playlist I created the chroma and timbre self similarity matrix for Underwater Acoustics and Cosi Lontano. Overall I can see more difference in the structure of self similarity matrix for different tracks in this playlist. Some songs are more self consistent than the others. The two example I picked are on the two side of the spectrum. “Underwater Acoustics” shows a high similarity across the whole song in both chroma and timbre. It does has some variations in the middle, but the variation parts still maintain a relatively high similarity level to the other parts of the music. “Cosi lontano” on the other hand shows a lot of changes in chroma and timbre among the track. It still sounds very consistent when you listen to it because there is a base percussion remain the same, but there are also different other instruments going on top of that.

Black

For the black playlist I created the chroma and timbre self similarity matrix for “Living nowhere with messy pigeons” and “Dagaz-Delusional circuits remix”. Overall there are more smaller segments and the changes happens more rapidly in the black playlist compare to the others. “Living nowhere with messy pigeons” is an intro so there are no drum beats. We can see both chroma and timbre varies a lot throughout the track. And there are smaller musical segments. In “Dagaz-Delusional Circuits Remix”, we can see three major parts from the checkerboard patterns, but there are also always some smaller variations, represent by the straight light lines.

Click here to listen to Living nowhere with messy pigeons
Click here to listen to Dagaz-Delusional circuits remix

white

In the similarity matrix for the white album, it shows similar patterns as the black since there are also smaller music segments and a lot of small variations. But it is overall more consistent compare to the black one. In “Synergy-Jupetto Mix” there are a lot of variations in chroma, because the melody was repeat playing with a change in key. The timbre has more gradual changes throughout the track, as we can see a horizontal shift from black to yellow. In “River words”, there are more consistency in chroma, but some small variations in timbre.

Click here to listen to Synergy-Jupetto Mix
Click here to listen to River words

Key histgram

I compared the distribution of keys within the four categories, where the darker color represents the major key and the lighter color represents the minor key. There are more major keys in pink and blue playlists compared to the black and white ones, which might contribute to a higher valence or positive emotional tone. In the pink playlist, there is a higher variation in keys that the tracks are evenly distributed across different keys. The black playlist on the other hand, shows a more concentrated distribution of keys, particularly centered around G major and B minor. In the white playlist C# is presented much more compare to the other playlists. Overall there are a lot of variety in the sharp and flat pitch classes in my corpus, but this cannot be directly associate with the complexity or the valence of the music.

Chordograms

I generated the chordograms for one of the most representative song track in each playlist. I applied euclidean distance metrics and manhattan norm. In the chordograms, there are more variations in the pink playlist. I displayed the one from the track Luna, where there is a repeat pattern of slight shifting downwards and shifting back in chords. In Soave from the blue playlist there are also some variation in the middle that deviate from the main chord. The black (Descending) and white (Dwelling) playlist have a relatively more stable chord pattern that is consistent throughout the track.

Tempo histgram

The tempo histograms reveal that the tempo across all four corpora tends to center around 120 bpm. However, the distribution of the tempo in the blue playlist appears to be more scattered compared to the others, indicating a greater variability in tempo within that playlist. In contrast, the pink and white playlist shows a very concentrated tempo distribution centered at around 125 bpm. As the corpus also included a few intro and outro tracks, it can explain the outliers with a tempo at around 100.

tempogram

I generated the tempogram for one song from each playlist. In the blue playlist there are a lot more variations in tempo compared to the other playlist. I plot the tempo graph for the song The Sea Breathe. It shows an average slow tempo with a fade in and a fade out. The tempo depicted on the tempogram s not very ascertained because there are no drum beats in this track. For the pink playlist I created the tempogram for Ofrenda - Alfred Czital Remix, it has a much higher tempo at around 135, and the tempo is very clear and consistent. With black playlist (Court of light) and white play list (Transparent creatures) it shows a similar pattern with an average tempo around 125.

K-Nearest Neighbors (KNN) classifier

I applied a K-Nearest Neighbors (KNN) classifier to distinguish the four playlists with different music album color. From the result we can see that the classifier is relatively more effective at identifying music in a white color album, and it has very low performance when identifying blue album. However the overall accuracy is only 20%, which means the probability of accurate prediction is lower than chance. It implies that either there is no clear difference in music with different color albums, or the differences can’t be identified from spotify api features.

CART Decision Tree

By using CART Decision tree for classification task, the accuracy raised to 37.5%.This classifier is very good at identify black playlists. The most important features identified by the classifier are: mode_key, energy, valence and tempo. However since the sample size is very small, the classifier might be over fitting the sample data instead of detecting the general pattern to identify color from audio features.